Many analyte measurement systems, such as self-monitoring blood glucose (SMBG) systems, clinical blood glucose monitoring systems and laboratory blood glucose monitoring systems, are based upon an amperometric, coulometric, potentiometric, voltammetric, or other electrical measurement of an electro-active species produced by a reaction with an analyte such as glucose or the measurement of a direct property of the analyte matrix. A combination of these methods also can be employed for calculating an analyte concentration.
In SMBG systems, an electrochemical measurement typically is performed by inserting a biosensor into a handheld meter and introducing a drop of a fluidic sample such as blood onto the biosensor having a defined sample space, a dried chemical reagent and a system of electrodes. Upon detecting the sample, the meter then performs the electrochemical measurement, and mathematical algorithms convert the response data into a reliable glucose concentration.
For example, in a single-potential, DC-based amperometric measurement, a potential is applied to a fluidic sample containing an electro-active analyte, and current is monitored as the analyte is reduced or oxidized. The resulting DC current exhibits a time decay, as described by the Cottrell equation. As the slope of the decay decreases and approaches a constant rate of change with respect to time, the magnitude of the current can be used to quantify the analyte.
The magnitude, rate and shape of the current decay, however, can be influenced by many variables including, but not limited to, reagent thickness, wetting of the reagent, rate of sample diffusion, Hct and temperature as well as presence of certain interferents. These interferents, or confounding variables, can cause an increase or decrease in the observed magnitude of the DC current that is proportional to an analyte such as glucose, thereby causing a deviation from the “true” glucose concentration.
Current methods and systems provide some advantages with respect to convenience; however, there remains a need for measurement methods that can correct or otherwise compensate for confounding variables.